Exploring Relationships between Dyadic-Level Factors and Collaborative Learning Outcomes with Social Robots

• In Event: DELT- Exploring Relationships between Dyadic-Level Factors and Collaborative Learning Outcomes with Social Robots

Short Description

Collaborative learning with social robots creates environments that combine human-human and human-robot interactions. These novel settings provide promising benefits but necessitate more research to better understand how these unique interactions impact learning. We used exploratory methods to investigate potential relationships between dyadic-level pre-existing factors, collaborative interactions, and subsequent learning outcomes. This works serves as a first step to understanding complex interactions with an emerging technology by utilizing data-mining techniques to derive hypotheses for future research.

Authors

• Presenter: Nikki G. Lobczowski, University of Pittsburgh

• Contributor: Christina Steele, University of Pittsburgh

• Contributor: Mingzhi Yu, University of Pittsburgh

• Contributor: Michael Diamond, University of Pittsburgh

• Contributor: Katherine Henriques, University of Pittsburgh

• Contributor: Adriana Kovashka, University of Pittsburgh

• Contributor: Diane J. Litman, University of Pittsburgh

• Contributor: Timothy James Nokes-Malach, University of Pittsburgh

• Contributor: Erin Walker, University of Pittsburgh